1. Field
The present disclosure relates generally to comparison of data sets describing manufactured products, and more particularly, to the comparison of multiple data sets of unlike structure including maximum configuration data sets containing all configuration data for a product subject to comparisons.
2. Background
Manufacturers of complex products, for example commercial jet aircraft, may maintain multiple and varied data stores containing information about the products. Detailed records may be stored before, during, and after manufacture and sale of an aircraft. The data stores may contain detailed engineering information including product specifications, design diagrams, assembly and parts descriptions, software information, change order information, maintenance data, and compliance documentation. Extensive engineering and other product information may be used in manufacturing operations as well as to support post-sale tracking of changes to aircraft in customer use. Manufacturers may be required to maintain accurate data about their products under contractual relationships with their customers and others and to comply with regulatory requirements.
Such manufacturers may maintain a plurality of internal data stores containing product information. Marketing, product design, engineering, manufacturing, field support, and executive functions may store and access product information from separate data stores. Some products may be manufactured from many thousands or more of component hardware parts as well as software programs and modules. Manufacturers face challenges in maintaining consistency within and across various data stores used by internal functions. Conflicts between internal product data store records may result in errors in manufacturing, causing delays and increasing manufacturing cost. Post-sale data conflicts may cause customer relationship problems and result in liability under warranty and maintenance commitments.
While a manufacturer of complex products may operate various internal data stores and face challenges associated with assuring consistency and accuracy across internal data stores, parties outside the manufacturer may also maintain similar data stores of the manufacturer's product information. Customers, partners, suppliers, subcontractors, regulators, and distributors of the manufacturer as well as post-sale service providers and regulatory bodies operate data stores containing the product information to support their own business and other operations. In addition to facing challenges presented by multiple internal data stores, the manufacturer may be interested in maintaining consistency between its internal data stores and those of outside parties. Further, the manufacturer seeks consistency between data stores of outside parties, for example between data stores of customers and those of service providers, such as maintenance firms. Such consistency between records of outside parties may support the manufacturer's warranty enforcement and post-sale parts and services revenue efforts. Long after a sale has been completed, the manufacturer may have a stake in consistency of information across its constituent customer, supplier, partner, and other relationships.
Challenges associated with data store consistency may arise from different data structures used by data stores maintained by groups internal to the manufacturer. External parties may also use different data structures and use different data naming conventions. In addition, both internal and external groups may not maintain current information in their data stores or may have differing version control practices.
To address risks and challenges of data stores not matching, a producer of complex manufactured products may use software programs that compare records in data stores and identify discrepancies between records. However, a manufacturer seeking accurate comparisons may be subject to limitations. The manufacturer may discover that data models of the data sets under comparison are different. Differences in data models may cause comparison results to be incorrect, misleading, and difficult to interpret. Further, methods of comparison may be limited in capability such that comparisons may be possible only between like units of the same product model. Comparisons of unlike models of a product may not be possible or be so limited in scope as to have minimal value. In addition, methods may be inflexible and not facilitate comparisons of groups of units, particularly groups of unlike or dissimilar models of product. Unit to unit comparisons may be the only comparisons that produce results of value, but such one-to-one comparisons are costly and time consuming when many units are involved.
Therefore, it would be advantageous to have a method and apparatus that takes into account one or more of the issues discussed above, as well as possibly other issues.